STAGEM: Saptiotemporal Analysis of Gastech Employees’ Movement Data
1 Singapore Management University
The VAST 2021 Mini Challenge 2 outlines a hypothetical scenario in which several GAStech employees have gone missing and the organisation, Protectors of Kronos (POK), is suspected of being involved. The challenge requires identification of suspicious activities hidden in data and determine any dubious people and locations that should be reported to the law enforcement using interactive visual analytical tools.
Our research and development effort aims to enable Kronos law enforcement with the ability to easily analyse, drill down and identify key suspects and suspicious locations, and thereby speeding up the investigation process.
The use cases of the data visualisation tool include but are not limited to the following:
The application aims to provide users actionable insights based on the following analyses:
The STAGEM Application was designed using R Shiny and hosted on shinyapps.io server. The application has 5 main section with various interactive visual analytics tools to allow users to investigate the data. The user guide to the application is available at https://isss608g1group5.netlify.app/userguide.html.
Figure 1: Abila Map
Figure 2: Scatter Plot of Locations visited
The tab allow users to investigate GASTech employee’s credit card transactions at the various locations made in Abila. There are three interactive visualisation that shares five filters where users can select by location, employee, date, time period of transaction and department of each employee to dynamically update the visualisations.
Figure 3: Heatmap
Figure 4: Boxplot
Figure 5: Stacked Barplot
Figure 6: Parallel Coordinate Plot
Figure 7: Network Analysis based on Credit Card Transactions
Future work would have to be done to integrate the different visualizations developed as the current plots are loosely coupled. One area of improvement would be to have pop-up charts upon clicking of data points on existing visualizations to showcase extended information that would be of relevance.
The scope of STAGEM could be extended to cover Mini-challenges 1 and 3 to provide a comprehensive integrated visual analytics system that helps to resolve the overarching case scenario. Additional analyses relating to mini-challenges 1 and 3 such as text analytics and sentiment analysis can help to complement findings from the existing application to provide a much more cohesive narrative to the storyline.
Through the utilisation of interactive visual analytical tools in the Shiny application, users can visualise patterns and anomaly activities of the employees. The user-friendly layout incorporated with drop down filters allow users to slice the data and utilise the interactivity of each visualization to investigate the data without knowledge of programming or data analytics.
We would like to thank Professor Kam Tin Seong for his guidance throughout the tenure of the project.
Our website can be found at https://isss608g1group5.netlify.app/. Alternatively, scan the QR code at the bottom left to access our website.
Code for the documents and applications can be found at https://github.com/jovinkahartanto/Visual-Analytics—Group-Project. Alternatively, scan the middle QR code at the bottom to access our Github.
Application can be assessed at https://limyongkai.shinyapps.io/ISSS608T5Shiny. Alternatively, scan the QR code on the bottom right to access our Shiny Application.
STAGEM: Saptiotemporal Analysis of Gastech Employees’ Movement Data